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Automatic evaluation-feedback system for automated social skills training.

Takeshi Saga1, Hiroki Tanaka2, Yasuhiro Matsuda3,4

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Automated social skills training (SST) systems can improve interpersonal communication accessibility. An evaluation-feedback system was developed, showing promising results for complementing human-led training.

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Area of Science:

  • Psychology
  • Computer Science
  • Rehabilitation Medicine

Background:

  • Social skills training (SST) is vital for interpersonal communication but faces accessibility challenges due to limited expert trainers.
  • Automated SST systems, particularly evaluation-feedback pipelines, are under development to address these limitations.

Purpose of the Study:

  • To develop an automated social skills training (SST) evaluation-feedback system.
  • To identify optimal feedback methods for automated SST through user studies.
  • To assess the performance of automated social skill score estimation models.

Main Methods:

  • Collected and analyzed a human-human SST dataset with diverse participants and clinical measures.
  • Developed an automated SST evaluation-feedback system supervised by experienced trainers.
  • Conducted a user study to evaluate feedback preferences (video, feedback ratio) and assess system performance.

Main Results:

  • Social skill score estimation models achieved a maximum Spearman's correlation of 0.68.
  • User studies indicated that recorded videos enhance understanding of areas for improvement.
  • Participants preferred a 2-positive/1-corrective feedback format, aligning with expert trainer practices.

Conclusions:

  • The developed automated SST evaluation-feedback system demonstrates practical potential.
  • This system can complement traditional SST, increasing accessibility and effectiveness.
  • Further development can enhance automated support for social skills development.